Data: monthly queries by country (clicks, impressions, ctr, position)
| 0 |
usa |
advertools |
40 |
60 |
0.666667 |
1.016667 |
2023-01-31 |
| 1 |
ind |
advertools |
21 |
35 |
0.600000 |
1.000000 |
2023-01-31 |
| 2 |
ind |
log analysis using python |
17 |
28 |
0.607143 |
1.000000 |
2023-01-31 |
| 3 |
gbr |
advertools |
15 |
25 |
0.600000 |
1.000000 |
2023-01-31 |
| 4 |
deu |
advertools |
10 |
20 |
0.500000 |
1.000000 |
2023-01-31 |
| ... |
... |
... |
... |
... |
... |
... |
... |
| 205890 |
zmb |
video sitemaps |
0 |
1 |
0.000000 |
63.000000 |
2023-09-30 |
| 205891 |
zwe |
crawling seo |
0 |
1 |
0.000000 |
95.000000 |
2023-09-30 |
| 205892 |
zwe |
download sitemap |
0 |
1 |
0.000000 |
12.000000 |
2023-09-30 |
| 205893 |
zwe |
get sitemap xml |
0 |
1 |
0.000000 |
47.000000 |
2023-09-30 |
| 205894 |
zwe |
seo library |
0 |
1 |
0.000000 |
64.000000 |
2023-09-30 |
205895 rows × 7 columns
Monthly metrics by page and country
| 0 |
https://advertools.readthedocs.io/ |
usa |
51 |
391 |
0.130435 |
47.304348 |
2023-01-31 |
| 1 |
https://advertools.readthedocs.io/en/master/advertools.logs.html |
ind |
49 |
688 |
0.071221 |
21.985465 |
2023-01-31 |
| 2 |
https://advertools.readthedocs.io/ |
ind |
28 |
108 |
0.259259 |
27.962963 |
2023-01-31 |
| 3 |
https://advertools.readthedocs.io/en/master/advertools.logs.html |
usa |
21 |
2350 |
0.008936 |
30.180851 |
2023-01-31 |
| 4 |
https://advertools.readthedocs.io/ |
gbr |
16 |
53 |
0.301887 |
32.056604 |
2023-01-31 |
| ... |
... |
... |
... |
... |
... |
... |
... |
| 24698 |
https://advertools.readthedocs.io/en/master/readme.html |
tun |
0 |
1 |
0.000000 |
1.000000 |
2023-09-30 |
| 24699 |
https://advertools.readthedocs.io/en/master/readme.html |
tur |
0 |
6 |
0.000000 |
16.666667 |
2023-09-30 |
| 24700 |
https://advertools.readthedocs.io/en/master/readme.html |
twn |
0 |
4 |
0.000000 |
42.250000 |
2023-09-30 |
| 24701 |
https://advertools.readthedocs.io/en/master/readme.html |
ukr |
0 |
2 |
0.000000 |
1.000000 |
2023-09-30 |
| 24702 |
https://advertools.readthedocs.io/en/master/readme.html |
vnm |
0 |
9 |
0.000000 |
15.333333 |
2023-09-30 |
24703 rows × 7 columns
Create interesting subsets of the data
Most frequent words
The wtd_freq column shows the total impressions of all queries containing the respective word. For example, “seo” has appeared in many different queries, the total impressions of which was 123,266.
We can now take the top words, create their respective regular expressions, and create special columns for each term.
| 0 |
brand |
advertool |
| 1 |
seo |
seo |
| 2 |
python |
python |
| 3 |
sitemap |
sitemap|xml |
| 4 |
analysis |
analy[sz]|analyt |
| 5 |
robots |
robots |
| 6 |
crawl |
crawl|scrap[ei]|spider |
| 7 |
log |
log(file)? |
| 8 |
search |
search |
| 9 |
serp |
serp |
| 10 |
google |
google |
| 0 |
advertools |
True |
False |
False |
False |
False |
False |
False |
False |
False |
False |
False |
| 1 |
advertools |
True |
False |
False |
False |
False |
False |
False |
False |
False |
False |
False |
| 2 |
log analysis using python |
False |
False |
True |
False |
True |
False |
False |
False |
False |
False |
False |
| 3 |
advertools |
True |
False |
False |
False |
False |
False |
False |
False |
False |
False |
False |
| 4 |
advertools |
True |
False |
False |
False |
False |
False |
False |
False |
False |
False |
False |
Top terms/topics across all queries
| python_term |
19.4% |
| robots_term |
16.8% |
| crawl_term |
14.7% |
| analysis_term |
11.7% |
| seo_term |
11.3% |
| sitemap_term |
10.4% |
| serp_term |
6.8% |
| search_term |
5.1% |
| google_term |
4.6% |
| brand_term |
0.5% |
| log_term |
0.0% |
Convert average positions to SERP page
| 0 |
get emoji |
52.333333 |
6 |
| 1 |
python web crawler |
80.500000 |
9 |
| 2 |
sitemaps.xml |
29.250000 |
3 |
| 3 |
test robots txt |
23.000000 |
3 |
| 4 |
unicode emoji search |
37.000000 |
4 |
| 5 |
how to print emoji in python |
42.000000 |
5 |
| 6 |
search engine 1000 videos |
21.000000 |
3 |
| 7 |
stop words in nlp |
51.000000 |
6 |
| 8 |
url list checker |
46.000000 |
5 |
| 9 |
serps com api |
82.000000 |
9 |
All reports and charts are made using the full dataset. You can easily use any subset based on available and newly-created columns/criteria
Country comparison (monthly impressions)
- Click a flag(s) to add/remove countrie(s)
Weighted word frequency - monthly (clicks)
- Total clicks for all keywords containing <word>.
- e.g.: in January, keywords containing “python” received a total of 323 clicks
Weighted bigram frequency - monthly (clicks)
Racing chart - impressions
Monthly impressions - map
Monthly impressions ~ clicks by country
- Zoom in to any part of the chart to focus on a certain set of countries (simply drag your mouse across the region/flags of interest)
Top pages monthly (impressions)
- This chart can be much more useful with larger sites (this one has only ~50 pages)
- Having URLs split, we can see how segments’ traffic have evoleved over time
dir_1, dir_2, or any combination